Conducting a job interview to hire AI developers can come as a real challenge.
How can you tell if someone’s a good fit?
How do you know what questions to ask?
The list goes on.
In this read, we’ll offer you some amazing interviewing techniques for AI Talent, along with some of the questions to ask the applicant.
Top 10 Interview Techniques & Questions: What Should You Ask?
Let’s look at top 10 questions, targeting different areas and skills.
Questions For Understanding The Fundamentals
Don’t dive too deep just yet. Initially, we want to know their understanding of the fundamental concepts.
Ask about their understanding of machine learning, neural networks, or natural language processing. The aim isn’t to stump them with complex queries. It’s more about gauging their comfort level with these foundational AI elements.
Perhaps a simple ‘how would you explain machine learning to a curious 10-year-old?’ could do the trick! By starting with a warm welcome and exploring the core concepts, you’re setting the stage for a smooth and insightful conversation with your potential AI developer!
Questions Assessing AI Developer Skills
It is extremely important to assess AI developers from a technical perspective—because that’s what is majorly demanded in their job role. You should:
Machine Learning (ML)
Measure their understanding of core ML concepts like supervised learning, unsupervised learning, reinforcement learning, and model evaluation metrics.
Interview Question: “Can you explain the key differences between supervised learning and unsupervised learning? Provide examples of real-world applications for each, and discuss the importance of model evaluation metrics in these contexts.”
Deep Learning (DL)
Assess their familiarity with neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers.
Explain a real-world AI application and ask them to break down the potential DL approach.
Interview Question: “Describe your experience with neural networks, especially convolutional neural networks (CNNs) and recurrent neural networks (RNNs). Can you break down a real-world AI application you’ve worked on and discuss the potential deep learning approaches?”
Problem Solving
Present them with an AI challenge relevant to your project or domain.
Observe their approach to defining the problem, identifying data sources, choosing appropriate algorithms, and evaluating potential solutions.
Interview Question: “Here’s a specific AI challenge related to our project. How would you approach defining the problem, identifying relevant data sources, choosing appropriate algorithms, and evaluating potential solutions? Walk me through your thought process“.
Practical Technical Experience
Ask about their past projects, focusing on AI-related ones.
Ask them to explain their role, the technical challenges they faced, and the solutions they implemented.
If possible, provide them with a small anonymized dataset from your project and ask them to build a basic model or perform some exploratory data analysis.
Interview Question: “Can you share details about a past AI-related project you’ve worked on? Explain your role, the technical challenges you encountered, and the solutions you implemented.”
Programming Languages and Libraries
Ensure they possess proficiency in languages like Python, R, and Java, along with popular AI libraries like TensorFlow, PyTorch, scikit-learn, and Keras.
Ask them to code a simple example using their preferred tools.
Interview Question:“Demonstrate your proficiency in programming languages by coding a simple example using Python, R, or Java. Additionally, showcase your familiarity with popular AI libraries like TensorFlow, PyTorch, scikit-learn, or Keras in the process.”
Questions Evaluating Soft Skills
Mastering the technical isn’t everything. While assessing technical skills and knowledge is crucial, an AI developer interviewer should also focus on technical and non technical aspects and key skills before hiring an AI developer. Let’s explore it:
Problem-solving approach:
Can the candidate handle complex problems systematically and creatively? Present them with an AI-related challenge and observe their thought process and methodology.
Interview Question: “Confronted with a complex AI-related problem, how do you systematically and creatively approach finding a solution? Walk me through your thought process and methodology.”
Communication skills:
Can they explain complex AI concepts clearly and concisely to both technical and non-technical audiences? Assess their ability to tailor communication to different stakeholders. Try to opt for those candidates having soft skills and technical skills at the same time. Take a look what key skills to look for when hiring AI developers.
Interview Question: “Can you explain a complex AI concept in a clear and concise manner, adapting your communication style for both technical and non-technical audiences? Provide an example from your past experience.”
Collaboration and teamwork:
AI projects often involve collaboration with engineers, data scientists, and other professionals. Evaluate the candidate’s ability to work effectively in a team and contribute constructively. Explore how diversity and inclusion in AI development teams make a difference.
Interview Question: “AI projects often require collaboration with diverse professionals. Share an example from your past work that highlights your ability to work effectively in a team and contribute constructively to achieve project goals.”
Ethical considerations:
As AI becomes increasingly powerful, understanding its ethical implications is vital. Evaluate the candidate’s awareness of potential biases and their commitment to responsible AI development, future of AI: emerging trends and technologies .
Interview Question: “As AI development carries ethical implications, how do you approach understanding and addressing potential biases in your work? Share your awareness of responsible AI development and any experiences dealing with ethical considerations in AI projects.”
What Are Some Other Effective AI Developer Interview Questions?
Many questions have to be asked during an interview with an AI developer.
Start by asking them about their portfolio or the projects on which they have worked.
This helps you in determining the skill set the candidate has.
Question: “Can you share a specific AI project you’ve worked on? What was your role, and how did your contributions impact the project’s success?”
It is beneficial to ask the specific language in which they have the expertise.
Ask if they know Java, Python, ASP.net, Swift, or Kotlin.
Question: “Which programming languages and AI frameworks are you proficient in? Can you discuss a challenging AI problem you solved using these tools?”
The best and the easiest way to understand if they are capable of managing a team or not is simple.
Just ask them a scenario-based question and see how they answer it.
Question: “How would you approach a very challenging scenario that you’ve never encountered before? Could you walk us through your problem-solving process?”
To know more about the candidate sitting right across the table, you have to ask them everything related to their profession.
Like, ask them about the outcomes of their projects and how they would deal with certain challenges during their time with you in the corporation.
Question: “Could you elaborate on the outcomes of a notable AI project you’ve been involved in? How did your contributions drive the project’s success?”
Question: “In an AI team setting, how do you convey complex AI concepts to non-technical team members? How important do you think effective communication is in an AI development team?”
Lastly, don’t forget the main question: what inspired them to become an AI developer?
Example Question: “What initially sparked your interest in AI? How do you envision contributing to the future of AI technology?”
Take your understanding of AI Job Market to the next level with our blog: “Navigating the AI Developer Job Market in 2024“.
Frequently Asked Questions (FAQs)
Q1. What questions to ask in a questionnaire about AI?
It might include questions on their practical experience with AI tools, projects they’ve worked on, or their understanding of AI’s impact on various industries.
Q2. What’s the difference between NLP and NLU?
NLP processes human language for tasks like translation or sentiment analysis. NLU helps understand context, meaning, and intent behind human language.
Q3. What is an agent in artificial intelligence?
In artificial intelligence, an agent refers to any entity capable of perceiving its environment through sensors and acting upon it using actuators.
Q4. What are the advantages and disadvantages of artificial intelligence?
AI advantages include enhanced efficiency, automation, accurate decision-making, and innovation. Disadvantages are job displacement, ethical concerns, data privacy issues, and reliance on technology.
